Transfer Learning Utilization for Banknote Recognition: a Comparative Study Based on Bosnian Currency

Almisreb, Ali Abd; Saleh, Mohamed A.

doi:10.21533/scjournal.v8i1.172

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…In a study by Mittal et al [15], MobileNet was used for 12160 images of Rupee banknote with 96.9% of recognition accuracy. Deep learning approach was also applied in study by Almisreb et al [31] where performance of pretrained CNN model including GoogLeNet, AlexNet and Vgg16 were compared using Bosnian currency. The related works in banknote recognition system implemented conventional Machine Learning and Deep Learning are summarized in Table 1.…”

Section: Banknote Recogntion Systemmentioning

confidence: 99%

Deep Learning Based Malaysian Coins Recognition for Visual Impaired Person

Sufri

Rosidi

As’ari

2022

AEJ

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Currency recognition has been widely developed using various types of techniques and able to assist people who have a visual impairment. Machine learning is one of the methods implemented where deep learning architecture is one of them. The deep learning approach is reliable and can be used in detection and recognition of objects based on images. As currency recognition has been developed for other currencies, thus in this project, currency recognition using Malaysian coins has been developed by modeling Convolutional Neural Network (CNN) in recognizing coin images. Malaysian coins dataset was developed consist of 2400 images of four classes of coins, 5 sen, 10 sen, 20 sen, and 50 sen. In this study, pretrained CNN which are AlexNet, GoogleNet, and MobileNetV2 were formulated in recognizing such coins. Performance of each trained model was evaluated using confusion matrix and GoogleNet obtained the best performance with 99.2% testing accuracy, 99.2% precision, 99.18% recall, and 99.19% F1 score. From the trained model, it can be further developed and implemented in assisting visually impaired persons by producing a prototype using Raspberry Pi and FPGA before it can be clinically tested on the subject.

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Section: Banknote Recogntion Systemmentioning

confidence: 99%

Deep Learning Based Malaysian Coins Recognition for Visual Impaired Person

Sufri

Rosidi

As’ari

2022

AEJ

View full text Add to dashboard Cite

show abstract

“…The recent advent of transfer deep learning has achieved successes in many areas such as classification and recognition [1]- [4]. One of the most promising visual object recognition applications is food recognition, since it helps to estimate food calories and analyze eating habits of people to maintain their health [5].…”

Section: Introductionmentioning

confidence: 99%